Application of Ultrahigh-Performance Liquid Chromatography and Electrospray Ionization Quadrupole Orbitrap High-Resolution Mass Spectrometry for Determination of 166 Pesticides in Fruits and Vegetables
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents an application of ultrahigh-performance liquid chromatography and electrospray ionization quadrupole Orbitrap high-resolution mass spectrometry (UHPLC/ESI Q-Orbitrap) for determination of 166 pesticide residues in fruits and vegetables. Pesticides were extracted from the samples using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure. UHPLC/ESI Q-Orbitrap MS (i.e., full MS scan) acquired full MS data for quantification, and UHPLC/ESI Q-Orbitrap dd-MS(2) (i.e., data-dependent scan) obtained product-ion spectra for confirmation. UHPLC/ESI Q-Orbitrap MS quantification was achieved using matrix-matched standard calibration curves with isotopically labeled standards or chemical analogues as internal standards. The method performance characteristics that included overall recovery, intermediate precision, and measurement uncertainty were evaluated according to a nested experimental design. For the matrices studied, about 90.3-91.5% of the pesticides had recoveries between 81 and 110%, 92.1-97.6% had intermediate precision ≤20%, and 89.7-95.2% had measurement uncertainty ≤40%. Confirmation was based on mass accuracy ≤5 ppm and LC retention time tolerance within ±2.5%. Overall, the UHPLC/ESI Q-Orbitrap has demonstrated great performance for quantification and confirmation of pesticide residues in fresh fruits and vegetables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it